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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 469 records · Page 26
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Data Systems Dynamic Simulator

The Data System Dynamic Simulator (DSDS) is a discrete event simulation tool. It was developed for NASA for the specific purpose of evaluating candidate architectures for data systems of the Space Station era. DSDS provides three methods for meeting this requirement. First, the user has access to a library of standard pre-programmed elements. These elements represent tailorable components of NASA data systems and can be connected in any logical manner. Secondly, DSDS supports the development of additional elements. This allows the more sophisticated DSDS user the option of extending the standard element set. Thirdly, DSDS supports the use of data streams simulation. Data streams is the name given to a technique that ignores packet boundaries, but is sensitive to rate changes. Because rate changes are rare compared to packet arrivals in a typical NASA data system, data stream simulations require a fraction of the CPU run time. Additionally, the data stream technique is considerably more accurate than another commonly-used optimization technique.

Rouff, Christopher↗
NASA NTRS1990

Economical graphics display system for flight simulation avionics

During the past academic year the focal point of this project has been to enhance the economical flight simulator system by incorporating it into the aero engineering educational environment. To accomplish this goal it was necessary to develop appropriate software modules that provide a foundation for student interaction with the system. In addition experiments had to be developed and tested to determine if they were appropriate for incorporation into the beginning flight simulation course, AERO-41B. For the most part these goals were accomplished. Experiments were developed and evaluated by graduate students. More work needs to be done in this area. The complexity and length of the experiments must be refined to match the programming experience of the target students. It was determined that few undergraduate students are ready to absorb the full extent and complexity of a real-time flight simulation. For this reason the experiments developed are designed to introduce basic computer architectures suitable for simulation, the programming environment and languages, the concept of math modules, evaluation of acquired data, and an introduction to the meaning of real-time. An overview is included of the system environment as it pertains to the students, an example of a flight simulation experiment performed by the students, and a summary of the executive programming modules created by the students to achieve a user-friendly multi-processor system suitable to an aero engineering educational program.

Source record↗
NASA NTRS1994

Common modeling system for digital simulation

The Joint Modeling and Simulation System is a tri-service investigation into a common modeling framework for the development digital models. The basis for the success of this framework is an X-window-based, open systems architecture, object-based/oriented methodology, standard interface approach to digital model construction, configuration, execution, and post processing. For years Department of Defense (DOD) agencies have produced various weapon systems/technologies and typically digital representations of the systems/technologies. These digital representations (models) have also been developed for other reasons such as studies and analysis, Cost Effectiveness Analysis (COEA) tradeoffs, etc. Unfortunately, there have been no Modeling and Simulation (M&S) standards, guidelines, or efforts towards commonality in DOD M&S. The typical scenario is an organization hires a contractor to build hardware and in doing so an digital model may be constructed. Until recently, this model was not even obtained by the organization. Even if it was procured, it was on a unique platform, in a unique language, with unique interfaces, and, with the result being UNIQUE maintenance required. Additionally, the constructors of the model expended more effort in writing the 'infrastructure' of the model/simulation (e.g. user interface, database/database management system, data journalizing/archiving, graphical presentations, environment characteristics, other components in the simulation, etc.) than in producing the model of the desired system. Other side effects include: duplication of efforts; varying assumptions; lack of credibility/validation; and decentralization in policy and execution. J-MASS provides the infrastructure, standards, toolset, and architecture to permit M&S developers and analysts to concentrate on the their area of interest.

Painter, Rick↗
NASA NTRS1992

Rapid development of the X-31 simulation to support flight-testing

The X-31 Enhanced Fighter Maneuverability Program has been recognized to form the International Test Organization, with the NASA Dryden Flight Research Facility (NASA-Dryden) as the responsible test organization. The two X-31 research aircraft and engineering support personnel were colocated at NASA-Dryden, with flight test operations beginning in Apr. 1992. Therefore, rapid development of a hardware-in-the-loop simulation was needed to support the flight test operations at NASA-Dryden, and to perform verification and validation of flight control software. The X-31 simulation system requirements, distributed simulation system architecture, simulation components math models to the visual system, and the advanced capabilities the X-31 simulation provides. In addition, unique software tools and the methods used to rapidly develop this simulation system will be highlighted.

Mackall, Dale↗
NASA NTRS1992

Rapid development of the X-31 simulation to support flight-testing

The X-31 Enhanced Fighter Maneuverability Program has been recognized to form the International Test Organization, with the NASA Dryden Flight Research Facility (NASA-Dryden) as the responsible test organization. The two X-31 research aircraft and engineering support personnel were colocated at NASA-Dryden, with flight test operations beginning in Apr. 1992. Therefore, rapid development of a hardware-in-the-loop simulation was needed to support the flight test operations at NASA-Dryden, and to perform verification and validation of flight control software. The X-31 simulation system requirements, distributed simulation system architecture, simulation components math models to the visual system, and the advanced capabilities the X-31 simulation provides. In addition, unique software tools and the methods used to rapidly develop this simulation system will be highlighted.

Mackall, Dale↗
NASA NTRS1989

A large scale software system for simulation and design optimization of mechanical systems

The concept of an advanced integrated, networked simulation and design system is outlined. Such an advanced system can be developed utilizing existing codes without compromising the integrity and functionality of the system. An example has been used to demonstrate the applicability of the concept of the integrated system outlined here. The development of an integrated system can be done incrementally. Initial capabilities can be developed and implemented without having a detailed design of the global system. Only a conceptual global system must exist. For a fully integrated, user friendly design system, further research is needed in the areas of engineering data bases, distributed data bases, and advanced user interface design.

Dopker, Bernhard↗
DOE OSTI2026

Temporal Coarse Graining for Classical Stochastic Noise in Quantum Systems

Simulations of quantum systems with Hamiltonian classical stochastic noise can be challenging when the noise exhibits temporal correlations over a multitude of time scales, such as for 1/f noise in solid-state quantum information processors. Here we present an approach for simulating Hamiltonian classical stochastic noise that performs temporal coarse-graining by effectively integrating out the high-frequency components of the noise. We focus on the case where the stochastic noise can be expressed as a sum of Ornstein-Uhlenbeck processes. Temporal coarse-graining is then achieved by conditioning the stochastic process on a coarse realization of the noise, expressing the conditioned stochastic process in terms of a sum of smooth, deterministic functions and bridge processes with boundaries fixed at zero, and performing the ensemble average over the bridge processes. For Ornstein-Uhlenbeck processes, the deterministic components capture all dependence on the coarse realization, and the stochastic bridge processes are not only independent but taken from the same distribution with correlators that can be expressed analytically, allowing the associated noise propagators to be precomputed once for all simulations. This combination of noise trajectories on a coarse time grid and ensemble averaging over bridge processes has practical advantages, such as a simple concatenation rule, that we highlight with numerical examples.

Albash, Tameem [Sandia National Lab. (SNL-NM), Alb↗
NASA NTRS2018

42: An Open-Source Simulation Tool for Study and Design of Spacecraft Attitude Control Systems

Simulation is an important tool in the analysis and design of spacecraft attitude control systems. The speaker will discuss the simulation tool, called simply 42, that he has developed over the years to support his own work as an engineer in the Attitude Control Systems Engineering Branch at NASA Goddard Space Flight Center. 42 was intended from the outset to be high-fidelity and powerful, but also fast and easy to use. 42 is publicly available as open source since 2014. The speaker will describe some of 42's models and features, and discuss its applicability to studies ranging from early concept studies through the design cycle, integration, and operations. He will outline 42's architecture and share some thoughts on simulation development as a long-term project.

Stoneking, Eric↗
DOE OSTI2025

A real-time distributed solid oxide electrolysis cell (SOEC) model for cyber-physical simulation

System integration and dynamic operability between SOEC and balance-of-plant (BoP) components are major technical challenges before realizing rapid load following of SOEC systems. Cyber-physical simulation (CPS) is a leading-edge digital engineering approach and is regarded as the next step beyond Digital Twins. CPS approach can be used to research SOEC system integration and develop dynamic controls prior to actual pilot testing without using a real SOEC. To seamlessly couple with BoP hardware and access non-observable operational parameters (e.g., local temperature gradient) during transients, a distributed one-dimensional (1D) real-time SOEC model was developed. Its real-time execution was demonstrated for 20 to 640 nodes at the fixed time step of 5 ms. A higher excess air ratio enabled smaller local temperature gradients on SOEC solid materials and faster transients upon current density step change from 0.15 to 0.55 A cm -2 . During the transients, the magnitude of the peak temperature gradient nearly doubled in 10 s from -3.5 to -5.9 °C cm -1 . This represents a significant operating risk that can impact the dynamic operability of SOEC systems. In addition, the local temperature gradient was found to change directions on all nodes in SOEC solid materials, with the greatest impact on the upstream nodes. The SOEC model was also tested at the thermal neutral voltage using actual process air flow parameters as variable model inputs. Variable process air temperatures were found to induce alternating local temperature gradients on SOEC solid materials. These are new operational mechanisms for SOEC degradation relevant for load following operational modes yet distinct from previous reports. To mitigate these unfavorable features, the SOEC can be operated at voltages that are slightly (±20 mV) deviated from the thermal neutral voltage. Here, the corresponding net thermal energy change was less than 1.6% of the electric power consumption. This 1D real-time SOEC model established the basis of cyber-physical simulation of SOEC hybrid systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗
NASA NTRS2012

Algorithm for Simulating Atmospheric Turbulence and Aeroelastic Effects on Simulator Motion Systems

Atmospheric turbulence produces high frequency accelerations in aircraft, typically greater than the response to pilot input. Motion system equipped flight simulators must present cues representative of the aircraft response to turbulence in order to maintain the integrity of the simulation. Currently, turbulence motion cueing produced by flight simulator motion systems has been less than satisfactory because the turbulence profiles have been attenuated by the motion cueing algorithms. This report presents a new turbulence motion cueing algorithm, referred to as the augmented turbulence channel. Like the previous turbulence algorithms, the output of the channel only augments the vertical degree of freedom of motion. This algorithm employs a parallel aircraft model and an optional high bandwidth cueing filter. Simulation of aeroelastic effects is also an area where frequency content must be preserved by the cueing algorithm. The current aeroelastic implementation uses a similar secondary channel that supplements the primary motion cue. Two studies were conducted using the NASA Langley Visual Motion Simulator and Cockpit Motion Facility to evaluate the effect of the turbulence channel and aeroelastic model on pilot control input. Results indicate that the pilot is better correlated with the aircraft response, when the augmented channel is in place.

Ercole, Anthony V.↗
NASA NTRS1981

Characteristics of flight simulator visual systems

The physical parameters of the flight simulator visual system that characterize the system and determine its fidelity are identified and defined. The characteristics of visual simulation systems are discussed in terms of the basic categories of spatial, energy, and temporal properties corresponding to the three fundamental quantities of length, mass, and time. Each of these parameters are further addressed in relation to its effect, its appropriate units or descriptors, methods of measurement, and its use or importance to image quality.

Statler, I. C.↗
NASA NTRS1992

Safer Weightlessness Simulator

System described in report simulates weightlessness of space for training of astronauts, without adverse effects of rapid decompression. As in previous simulators, trainee wearing space-suit performs training exercises while immersed in water. In new system, space-suit interior is not above atmospheric pressure. No need for trainee to undergo gradual decompression to prevent bends after lengthy exercise; nor is there need for medical team to be present.

Vykukal, Hubert C.↗